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Showing 11 - 15 of 86 results.

AGBTPH19 - Navigating the Regulatory Landscape for All of Us Genotyping and Whole Genome Sequencing Processes

Niall Lennon1, Kim Doheny2, Donna Muzny3, Christina Lockwood4, Ginger Metcalf3 on behalf of the members of the All of Us Regulatory Working Group

 

1Broad Institute of MIT and Harvard, Cambridge, MA; 2Johns Hopkins University, Baltimore, MD; 3Baylor College of Medicine, Houston TX; 4Northwest Genomics Center, University of Washington, WA

 

The All of Us Research Program (AoURP) is a large collaborative initiative sponsored by the National Institutes of Health (NIH) with a primary objective of building a research resource composed of participant-provided information (PPI), including environmental, physiologic, and health data and biospecimens from 1 million or more research participants who reflect the diversity of the U.S. Participants are also invited to undergo physical measurements and provide biospecimens from which genomic information and other biomarkers will be derived. 

 

A core value of the program is that participants will have access to their data and that they may receive information potentially relevant to their own health. To this end, the program will include a return of results arm, in which predispositions to the development of certain diseases will be assessed through examination of a panel of genes (termed the AoU Medically Actionable Panel) and high confidence pharmacogenetic variants. Primary testing will involve Whole Genome Sequencing (WGS) as well as a custom genotyping array (AoU Array). Both assays have been validated as lab-developed tests (LDTs) by a group of CAP/CLIA certified clinical labs in genome centers across the US (Broad Institute, Baylor College of Medicine, Johns Hopkins, and the UW Northwest Genome Center). 

 

Since health-related and potentially actionable information is being returned to healthy individuals who have not had a physician-ordered clinical test for a specific condition, the US FDA has determined that this represents a high risk activity and therefore requires an Investigational Device Exemption (IDE). We present here the process of navigating the IDE pre-submission and submission process for this large, multi-center genomic testing project.

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AGBTPH19 - Comparison of Blood Collection Vacutainers for Reduction of gDNA Contamination in cfDNA Studies

Emily Moore1, Evan McDaid1, Katie Larkin1, Michelle Cipicchio1, Nicholas Fitzgerald1, Michael Nasuti1, Brendan Blumenstiel1, Tim DeSmet1, Viktor Adalsteinsson1, Niall Lennon1, Stacy Gabriel1 

 

1Broad Institute of MIT and Harvard, Cambridge, MA

 

Liquid biopsy and cfDNA sequencing allows for rapid analysis of cancer progression in the field of precision medicine. Successful library construction of a cfDNA sample is dependent upon the ability to purify cfDNA in the absence of gDNA. Throughout the sample collection and handling process, liquid biopsy samples may be subjected to cell lysis, resulting in the release of gDNA, negatively affecting sample integrity. Therefore, controlling variables in the sample collection process is an important factor in improving the resulting variant detection. Vacutainers and the various stabilizers within them function to postpone gDNA contamination. As minimizing gDNA presence is critical for successful sequencing, it is important to utilize a vacutainer that provides the greatest degree of sample integrity. 

 

We evaluated seven vacutainers across multiple time points over a 32-day period to determine their relative stability. Whole blood collected from four unique healthy donors was fractionated at predetermined time intervals. The comparison was performed over a large window of time which allowed for changes in the relative abundance of gDNA to be identified, as well as determining success in ultra-low-pass whole-genome sequencing at 0.1X coverage. 

 

Analysis of concentration, DNA fragment size, and sequencing results were used to determine vacutainer performance in reducing gDNA contamination. Through this analysis we observed there is a relationship between vacutainer type and degree of gDNA contamination over time. Collecting this information will allow for a recommendation on which tube type should be utilized for blood collection, as well as the optimal time frame from collection to fractionation to avoid gDNA contamination, improving a sample’s chance of success in sequencing. Fine-tuning this aspect of sample collection will be particularly impactful for clinical applications where sample integrity and mutation detection will ultimately have an effect on a patient’s diagnosis, treatment and disease outcome.

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AGBTPH19 - A Scalable Liquid Biopsy Pipeline Using Duplex Sequencing

Mark Fleharty1, Madeleine Duran1, Matt DeFelice1, Brenden Blumensteil1, Carrie Cibulskis1, Viktor Adalsteinsson1, Stacey Gabriel1, Niall Lennon1

 

1Broad Institute of MIT and Harvard, Cambridge, MA

 

Liquid biopsies are a relatively non-invasive procedure enabling greater access to patient specimens and allows for the characterization of somatic variants repeatedly over time. With this ability to accurately detect somatic events, liquid biopsy has the potential to significantly impact the course of precision medicine in cancer.

 

We present an end-to-end pipeline that delivers high quality liquid biopsy results to support translational research.  Using a custom data pipeline and a lab process that incorporates duplex unique molecular indices (UMI) we have benchmarked a 396 gene pan-cancer panel, a multiple myeloma panel, and glioma panel. This pipeline makes use of UMIs for increasing the available depth of reads and reduces error by utilizing duplex-consensus called reads.  We have benchmarked this technology using pooled sample analysis to simulate somatic variants from a tumor and normal-normal analysis as an independent measure of false positive rate. Our pipeline produces duplex consensus called bams and variant calls. We have developed a set of novel variant filters specific to duplex consensus calls that are not found in other types of somatic pipelines.  With these novel filters, our liquid biopsy pipeline achieves a false positive rate under 0.5 per megabase with > 90% sensitivity at 1% allele fraction.

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AACR19 Poster - Innovations in large scale liquid biopsy

Carrie Cibulskis1, Brendan Blumenstiel1, Matthew DeFelice1, Mark Fleharty1, Justin Abreu1, Viktor Adalsteinsson2, Laxmi Parida3, Susanna Hamilton1, Gad Getz4, Niall Lennon11Broad Institute, Cambridge, MA; 2Broad Institute, Koch Institute, Massachusetts General Hospital, Cambridge, MA; 3IBM, Cambridge, MA; 4Broad Institute, Harvard Medical School, Massachusetts General Hospital, Cambridge, MA

Abstract
Broad Genomics offers a comprehensive liquid biopsy sequencing platform designed to provide the optimal flexibility for conducting research studies in a broad range of applications including: biomarker discovery, treatment resistance monitoring, and clinical grade ctDNA profiling. By utilizing low cost, low coverage whole genome sequencing in conjunction with dual unique molecular indexed (UMI) libraries we can offer a range of analysis that allow researchers to select the most appropriate samples for whole exome profiling or for deeper coverage, higher sensitivity targeted gene panels. To date we have generated over 3000 liquid biopsy whole genome copy number profiles and purity estimates and are supporting driver projects including the Broad/IBM Cancer Resistance Project and Count Me In. The study design for the Broad/IBM effort takes advantage of the discovery potential of tissue-based sequencing combined with serial liquid biopsy analysis to elucidate resistance events by tracking clonal and subclonal populations in patient samples over time. Sourcing samples for this and other similar efforts is a major undertaking and a combination of methods for maximally broad and deep genomic profiling are required to assay patients throughout the course of care, as tumor fraction in blood fluctuates. Responding to this need, and other applications requiring increased sensitivity we have developed a high throughput, automated workflow to efficiently assay cfDNA samples with lower tumor content. Benchmarking data using healthy donor pooled cfDNA samples indicates our assay is capable of detecting > 90% of variants present at ~1% minor allele fraction with less than 1 false positive variant called per megabase. This established laboratory and analytic process forms the basis of our 2Mb, 400 gene CLIA targeted assay currently undergoing validation. Through this suite of products we hope to enable an expansion of cfDNA sequencing efforts in support of clinical and research applications. Early results from emerging studies utilizing this platform to be presented.
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AACR19 Poster - Somatic Analysis In the Cloud - TAG

Junko Tsuji, Andrew Hollinger, Alyssa MacBeth, Brian R. Grander, Micah Rickles-Young, Tera Bowers, Carrie Cibulskis, Niall Lennon. Broad Institute of MIT and Harvard, Cambridge, MA 

Abstract
With advances in high-throughput sequencing technologies and analytical tools, genomic analysis of tumors has led to the identification of various important somatic mutations that shed light on diagnosis, prevention, and treatment for cancer. However, detecting somatic variants is not a trivial task in terms of the technical aspects (e.g. filtering germline events and removing a variety of noises in tumor samples) and computational resources to handle large-scale cohort analysis. There is also a demand for maintaining stable software versions and the workflows for studies over extended periods of time, that need consistency and traceability, such as clinical trials. We introduce here, the Translational Analysis Group (TAG), a team which deploys, validates, and conducts scalable analytical workflows in a secure, cloud-based environment. We maintain 29 well-tested workflows with best practice methods and ample resources for both somatic and germline analysis. Our cloud platform, FireCloud, enables us to run workflows at any scale. Since May 2017, our team has performed nearly 10,000 analyses for mutation detection (SNV, InDel, CNV, and SV) and cohort analysis on tumor samples and cell-free DNA samples. TAG offers a range of options for somatic and germline variant detection, from legacy pipelines through recently validated contemporary pipelines to allow for continuity across long running projects.
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